I use the fire incident dispach from opendata of NewYork
library(dplyr)## Warning: il pacchetto 'dplyr' è stato creato con R versione 4.2.3##
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library(mapview)## Warning: il pacchetto 'mapview' è stato creato con R versione 4.2.3library(sf)## Warning: il pacchetto 'sf' è stato creato con R versione 4.2.3## Linking to GEOS 3.9.3, GDAL 3.5.2, PROJ 8.2.1; sf_use_s2() is TRUElibrary(geojsonio)## Warning: il pacchetto 'geojsonio' è stato creato con R versione 4.2.3## Registered S3 method overwritten by 'geojsonsf':
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## print.geojson geojson
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## prettylibrary(leaflet) ## Warning: il pacchetto 'leaflet' è stato creato con R versione 4.2.3library(broom)## Warning: il pacchetto 'broom' è stato creato con R versione 4.2.3fire_data <- read.csv("Fire_Incident_Dispatch_Data_last_50k.csv")
alarm_box_loc <- read.csv("Alarm_Box_Locations.csv")
firefighter_stations <- read.csv("fdny-firehouse-listing.csv")fire_data$ALARM_BOX_NUMBER <- as.character(fire_data$ALARM_BOX_NUMBER)
fire_data$INCIDENT_BOROUGH <- as.factor(fire_data$INCIDENT_BOROUGH)
fire_data <- fire_data %>% rename(al_number = ALARM_BOX_NUMBER, borough = INCIDENT_BOROUGH)
firefighter_stations$Borough <- as.factor(firefighter_stations$Borough)
firefighter_stations <- firefighter_stations %>% rename(borough = Borough)
alarm_box_loc_new <- alarm_box_loc %>% select(BOROBOX, LATITUDE, LONGITUDE) %>%
rename(al_number = BOROBOX, lat = LATITUDE, lon = LONGITUDE)
fire_data <- fire_data %>%
mutate(al_number = str_pad(al_number, width = 4, pad = "0"))fire_data_new <- fire_data %>%
mutate(al_number = case_when(
borough == "BRONX" ~ paste0("X", al_number),
borough == "BROOKLYN" ~ paste0("B", al_number),
borough == "MANHATTAN" ~ paste0("M", al_number),
borough == "QUEENS" ~ paste0("Q", al_number),
borough == "RICHMOND / STATEN ISLAND" ~ paste0("R", al_number),
TRUE ~ al_number
))fire_data_merged <- merge(fire_data_new, alarm_box_loc_new, by = "al_number", all.x = TRUE)
fire_data_merged <- na.omit(fire_data_merged)
firefighter_stations <- na.omit(firefighter_stations)alarm_inc_count <- fire_data_merged %>%
group_by(al_number, lat, lon) %>%
summarise(Count = n()) %>%
rename(incident_count = Count)## `summarise()` has grouped output by 'al_number', 'lat'. You can override using
## the `.groups` argument.alarm_inc_count_sdf <- st_as_sf(alarm_inc_count, coords = c("lon", "lat"), crs = 4326)count_inc_brough <- count(fire_data_merged, borough)
count_inc_brough <- count_inc_brough %>% rename(incident_count = n)
count_inc_brough <- count_inc_brough %>% mutate(borough = recode_factor(borough, "BRONX" = "Bronx", "BROOKLYN" = "Brooklyn", "MANHATTAN" = "Manhattan", "QUEENS" = "Queens", "RICHMOND / STATEN ISLAND" = "Staten Island"))
count_inc_brough## borough incident_count
## 1 Bronx 4882
## 2 Brooklyn 7867
## 3 Manhattan 7094
## 4 Queens 5756
## 5 Staten Island 1350firefighter_stations <- firefighter_stations %>% rename(lat = Latitude, lon = Longitude)
firefighter_stations_sdf <- st_as_sf(firefighter_stations, coords = c("lon", "lat"), crs = 4326)
head(firefighter_stations_sdf)## Simple feature collection with 6 features and 10 fields
## Geometry type: POINT
## Dimension: XY
## Bounding box: xmin: -74.01252 ymin: 40.70347 xmax: -73.9929 ymax: 40.71976
## Geodetic CRS: WGS 84
## FacilityName FacilityAddress
## 1 Engine 4/Ladder 15 42 South Street
## 2 Engine 10/Ladder 10 124 Liberty Street
## 3 Engine 6 49 Beekman Street
## 4 Engine 7/Ladder 1/Battalion 1/Manhattan Borough Command 100-104 Duane Street
## 5 Ladder 8 14 North Moore Street
## 6 Engine 9/Ladder 6 75 Canal Street
## borough Postcode Community.Board Community.Council Census.Tract BIN
## 1 Manhattan 10005 1 1 7 1000867
## 2 Manhattan 10006 1 1 13 1075700
## 3 Manhattan 10038 1 1 1501 1001287
## 4 Manhattan 10007 1 1 33 1001647
## 5 Manhattan 10013 1 1 33 1002150
## 6 Manhattan 10002 3 1 16 1003898
## BBL
## 1 1000350001
## 2 1000520022
## 3 1000930030
## 4 1001500025
## 5 1001890035
## 6 1003000030
## NTA
## 1 Battery Park City-Lower Manhattan
## 2 Battery Park City-Lower Manhattan
## 3 Battery Park City-Lower Manhattan
## 4 SoHo-TriBeCa-Civic Center-Little Italy
## 5 SoHo-TriBeCa-Civic Center-Little Italy
## 6 Chinatown
## geometry
## 1 POINT (-74.00754 40.70347)
## 2 POINT (-74.01252 40.71007)
## 3 POINT (-74.00525 40.71005)
## 4 POINT (-74.00594 40.71546)
## 5 POINT (-74.00668 40.71976)
## 6 POINT (-73.9929 40.71521)Downloand of the GEO JSON
geojson_newyork <- geojson_read("NYC_BoroughBoundaries.geojson", what = "sp")
geojson_newyork <- setNames(geojson_newyork, c("borough_code", "borough", "shape_area", "shape_leng"))
geojson_newyork$borough <- as.factor(geojson_newyork$borough)
geojson_newyork$borough_code <- NULL
head(geojson_newyork)## class : SpatialPolygonsDataFrame
## features : 5
## extent : -74.25559, -73.70001, 40.49613, 40.91553 (xmin, xmax, ymin, ymax)
## crs : +proj=longlat +datum=WGS84 +no_defs
## variables : 3
## names : borough, shape_area, shape_leng
## min values : Bronx, 1187174772.5, 325917.35395
## max values : Staten Island, 636520502.758, 888199.731385geojson_newyork@data = data.frame(geojson_newyork@data, count_inc_brough[match(geojson_newyork@data$borough, count_inc_brough$borough),])
geojson_newyork@data$borough.1 <- NULLmapview(list(firefighter_stations_sdf, geojson_newyork),
zcol = list(NULL, "incident_count"),
legend = list(FALSE, TRUE),
homebutton = list(FALSE, TRUE), layer.name = list(NULL, "indicents_number"), alpha.regions = 0.5, aplha = 1)mapview(list(alarm_inc_count_sdf, geojson_newyork),
zcol = list("incident_count", "borough"),
legend = list(TRUE, TRUE),
homebutton = list(TRUE, TRUE),
layer.name = list("incident_count", "brorough"),
alpha.regions = list(0.7, 0.4),
aplha = list(1, 1))